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Conference papers

Reproducible Performance Optimization of Complex Applications on the Edge-to-Cloud Continuum

Daniel Rosendo 1, 2 Alexandru Costan 3, 1 Gabriel Antoniu 1 Matthieu Simonin 4 Jean-Christophe Lombardo 2 Alexis Joly 2 Patrick Valduriez 2 
1 KerData - Scalable Storage for Clouds and Beyond
Inria Rennes – Bretagne Atlantique , IRISA-D1 - SYSTÈMES LARGE ÉCHELLE
2 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
4 MYRIADS - Design and Implementation of Autonomous Distributed Systems
Inria Rennes – Bretagne Atlantique , IRISA-D1 - SYSTÈMES LARGE ÉCHELLE
Abstract : In more and more application areas, we are witnessing the emergence of complex workflows that combine computing, analytics and learning. They often require a hybrid execution infrastructure with IoT devices interconnected to cloud/HPC systems (aka Computing Continuum). Such workflows are subject to complex constraints and requirements in terms of performance, resource usage, energy consumption and financial costs. This makes it challenging to optimize their configuration and deployment. We propose a methodology to support the optimization of real-life applications on the Edge-to-Cloud Continuum. We implement it as an extension of E2Clab, a previously proposed framework supporting the complete experimental cycle across the Edge-to-Cloud Continuum. Our approach relies on a rigorous analysis of possible configurations in a controlled testbed environment to understand their behaviour and related performance trade-offs. We illustrate our methodology by optimizing Pl@ntNet, a world-wide plant identification application. Our methodology can be generalized to other applications in the Edge-to-Cloud Continuum.
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Submitted on : Tuesday, August 3, 2021 - 7:37:07 PM
Last modification on : Tuesday, July 5, 2022 - 9:50:45 AM
Long-term archiving on: : Thursday, November 4, 2021 - 6:23:56 PM



Daniel Rosendo, Alexandru Costan, Gabriel Antoniu, Matthieu Simonin, Jean-Christophe Lombardo, et al.. Reproducible Performance Optimization of Complex Applications on the Edge-to-Cloud Continuum. Cluster 2021 - IEEE International Conference on Cluster Computing, Sep 2021, Portland, OR, United States. ⟨10.1109/Cluster48925.2021.00043⟩. ⟨hal-03310540⟩



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